Title: Intelligent technique and its application in fault diagnosis based on granular computing

Authors: Zhousuo Zhang, Xiaoxu Yan, Wei Cheng

Addresses: Department of Mechanical Engineering, State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an 710049, China. ' Department of Mechanical Engineering, State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an 710049, China. ' Department of Mechanical Engineering, State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an 710049, China

Abstract: This paper presents a new approach to intelligent fault diagnosis of the machinery based on granular computing. The tolerance granularity space mode is constructed by means of the inner-class distance defined in the attributes space. Different features of the vibration signals, including time-domain statistical features and frequency domain statistical features, are extracted and selected using distance evaluation technique as the attributes to construct the granular structure. Finally, the proposed approach is applied to fault diagnosis of rolling element bearings, and testing results show that the proposed approach can reliably recognise different faulty categories and severities.

Keywords: granular computing; tolerance relations; granularity structure; fault diagnosis; intelligent diagnosis; vibration signals; rolling element bearings.

DOI: 10.1504/IJGCRSIS.2010.036979

International Journal of Granular Computing, Rough Sets and Intelligent Systems, 2010 Vol.1 No.4, pp.370 - 381

Received: 02 Feb 2009
Accepted: 02 Feb 2009
Published online: 20 Nov 2010 *

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